Statistical process control (SPC) is an approach to evaluate processes whether they are in statistical control or not. For this aim, control charts are generally used. Since sample data may include uncertainties coming from measurement systems and environmental conditions, fuzzy numbers and/or linguistic variables can be used to capture these uncertainties. In this paper, one of the most popula...

in statistical quality control a very widely used measure is average run length (arl) which may be worked out by different methods like integral equation, approximations, and monte carlo simulations. the arl measure and the other related measures are of major significance in every type of production process. an omission in its computation (and hence its related measures such as extra quadratic ...

Process monitoring through control charts is a quite popular practice in statistical process control. From a statistical point of view, a superior control chart is one that has an efficient design structure, but having resistance against unusual situations is of more practical importance. To have a compromise between the statistical and practical purposes, a natural desire is to have a control ...

Double sampling (DS) X-control charts are designed to allow quick detection of a small shift of process mean and provides a quick response in an agile manufacturing environment. However, the DS X-control charts assume that the process standard deviation remains unchanged throughout the entire course of the statistical process control. Therefore, a complementary DS chart that can be used to moni...

The principal function of a control chart is to help management distinguish different sources of variation in a process. Control charts are widely used as a graphical tool to monitor a process in order to improve the quality of the product. Chen and Hsieh (2007) have designed a T2 control chart using a Variable Sampling Size and Control limits (V SSC) scheme. They have shown that using the V SSC...

Although the percentile-based control charts are very effective with guaranteed in-control and out-of-control run lengths in statistical process control, they still lack algorithmic (especially) software support. The proposed (pbcc) tool fills this gap. This is freely available implements recent work on individual as well joint charts.

One of the primary tools used in statistical quality control is the control charts. The standard assumptions that are usually cited in justifying the use of control charts are that the data generated by the in control process are independent and identically distributed. However the independency assumption is not realistic in practice. Data sets collected from industrial processes may have corre...

Process monitoring through control charts is a quite popular practice in statistical process control. This study is planned for monitoring the process dispersion parameter using exponentially weighted moving average (EWMA) control chart scheme. Most of the EWMA dispersion charts that have been proposed are based on the assumption that the parent distribution of the quality characteristic is nor...

The control chart is a very popular tool of statistical process control. It is used to determine the existence of special cause variation to remove it so that the process may be brought in statistical control. Shewhart-type control charts are sensitive for large disturbances in the process, whereas cumulative sum (CUSUM)–type and exponentially weighted moving average (EWMA)–type control charts ...

Currently, vibration-based damage detection is an area of significant research activity. This paper attempts to extend the research in this field through the application of statistical analysis procedures to the vibration-based damage detection problem. The damage detection process is cast in the context of a statistical pattern recognition paradigm. In particular, this paper focuses on applyin...